At the heart of our present day sharing economy is the often lauded, sometimes corrupted, and occasionally controversial open source model. Though the open source model has its roots in the early days of automobile development, our Internet age has proved an ideal medium for free licensing and distribution.

The world’s biggest names in technology – particularly those in Silicon Valley – have released their artificial intelligence technology via the open source model over the past few months in a domino effect that has made some of the most sophisticated AI programs available to anyone with Internet connection. In huge maneuvers, Google, Facebook, Microsoft, and China’s search engine giant Baidu have taken deep learning even deeper.

In November of last year, Google open sourced the software library for TensorFlow, the tech giant’s perceptual and language comprehension program. Though TensorFlow wasn’t the first open source AI software out there – software such as Torch, Caffe, and Theano – it is widely regarded as some of the most advanced AI algorithms in the world. Thus Google’s move to make TesorFlow open source marked an unparalleled step forward, which its competition couldn’t resist but to follow.

When the company announced its decision last year, Google engineer Jeff Dean told Wired Magazine they’d open TensorFlow in hopes that “…the [AI] community adopts this as a good way of expressing machine learning algorithms of lots of different types, and also contributes to building and improving [TensorFlow] in lots of interested ways.” In other words, Google may have maintained a competitive edge by keeping its code to itself, but they realized they’re software would be even more productive if unaffiliated programmers could toy with it, add to it, and share their developments. This sentiment would be shared by fellow tech giants.

By the end of the second week of the new year, Baidu announced the release of its WARP-CTC C library and optional Torch bindings on GitHub. The available downloads included the Chinese company’s speech recognition software, which last year they showed was so sophisticated, it could rival the ability of its human counterparts in some cases. A video of the company’s facial recognition software – launched last year for Halloween – depicts some of their AI in action.

In the latest release, Microsoft followed suit and released it’s AI toolkit – called CNTK – on GitHub. Like Baidu, Microsoft’s software focuses on deep learning and speech recognition. Like Google, Facebook, and Baidu, the company’s release is seen both as a collaborative effort and one which may prove valuable to their efforts to advance their technology.

At first glance it might seem like releasing trade secrets would undermine these companies’ competitive edges – but these moves are widely regarded as wise ways for the tech giants to round up the collaborative efforts of independent developers. It will be exciting to watch how these open sourced softwares and hardware will be polished for all in the coming year. Stay tuned or even join in to collaborate by following the links above.

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IBM has entered into the open-source software competition, with giants Facebook and Google, by making its SystemML available for public modification through the Apache Software Foundation. The nearly decade-old program could help developers customize machine-learning software for the purpose of an institution's needs. The system is designed to work with Spark software, capable of processing bulk data arriving from continuous sources such as mobile phones. The reasons behind the open program release are multi-faceted, but include recruiting new AI experts and talent.

A few weeks ago, Chinese software company Baidu released key parts of a key artificial intelligence/ speech recognition algorithm into the realm of open source, following in the footsteps of Facebook and Google last year.

It's been over a month since our last major artificial intelligence consensus (which covered 33 AI researcher perspectives on the 20-year risks of AI), and we decided that this time around, we'd speak with AI executives directly about the future of artificial intelligence and machine learning in consumer tech. The media is awash with buzz-stories about autonomous vehicles, speech recognition, robotics, and more, but it seems difficult to glean a perspective on which consumer AI tech trends are likely to make the biggest impact in the coming 5 years. While there's certainly no crystal ball, our preference as a market research firm is to combine research and news analysis with a strong consensus from dozens of experts in the field. When it comes to AI for consumer tech, we decided to ask executives and founders of artificial intelligence companies what they believe to be the most important AI consumer tech trends in the next half decade. You can see a full list of the answers to our "AI Consumer Tech Trends" below in our large infographic.

Episode Summary: If there's any industry ripe for disruption by AI and ML applications, it's healthcare. This week, we speak with Eleven Two Capital's Founder and Managing Partner Shelley Zhuang, whose investment focus (among other spaces) is on innovative healthcare services and applications. In addition to discussing how AI and ML is helping propel genomics, diagnostics, therapeutic treatment, and other innovations into a new paradigm, she touches on what the healthcare space might look like in the next 10 years. For healthcare startups looking to break into the healthcare market, Zhuang doesn't pretend to have simple answers; however, she identifies commonalities among smart companies that have prepared early for meeting regulatory and other industry considerations. This interview was recorded live in San Francisco at Re-Work's Machine Intelligence in Autonomous Vehicles Summit in March 2017.

A few weeks ago, Chinese software company Baidu released key parts of a key artificial intelligence/ speech recognition algorithm into the realm of open source, following in the footsteps of Facebook and Google last year.

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